The Missing Link Part 2
At Coalesce 2022 we talked about how design is the “missing link”between “data” and “profit”, especially for technical folks (or people who want to get more technical).
The four lessons we took away from fashion design were:
there’s more to “being technical” than just code
ideation, design, and fabrication are iterative activities, not linear steps
good design can make up for bad fabrication, but not vice versa
“analytics designers” are the best at tackling complex problems
Great design skills are often more important than advanced technical skills when it comes to delivering enterprise value as someone doing analytics or ML engineering.
In this context, “design” means the (iterative) process of choosing appropriate methods and tools to implement a data solution. For example, in order of increasing risk/scope:
choosing how to structure the CTEs and intermediate models for an individual dbt mart model
operationalizing a new ML model
deciding which team should own a new data transformation
determining how to structure your data warehouse
selecting the data stack for your company
In each of these cases, it will be the solution’s overall design—not its nitty-gritty technical details—that determines how successful it is.
Whether you want to expand your team’s design skills or advocate for the skills that are already there, the next question is: how can design skills be evaluated?
Design’s component skills
If the best engineers are great designers—what makes a great designer?
Essentially, great designers are able to come up with multiple viable solutions for a problem and reliably choose an appropriate solution for the problem at hand. Importantly, this is usually not going to be the “most technically correct” solution.
My intro to graphic design professor emphasized to the class that when you’re working as a professional designer, “Nobody gives a shit about what you like. They care about what works.”
“Design” is an expansive and deep skill set, and there are a lot of different ways to break it down. I’m going to focus on these five component skills: observation, understanding, creativity, synthesis, and decisiveness.
Usually, an individual will be better at some of these than others, highlighting potential areas for teamwork or personal development.
Sometimes, one or more of these steps will be blocked by organizational issues—such as a lack of access to stakeholders, a lack of time allowance for true creativity and synthesis, or a lack of opportunities for decision-making.
For each of the five questions, I’ll share some behavioral interview questions that can help you assess these skills—many of which I’ve used in actual interviews.
If you’re an analytics engineer, try to answer those questions. What examples would you provide? How many do you have to choose from? Is this an area you might want to develop more?
If you’re a manager, consider asking your team these questions to assess how they’re doing in each of the five areas. Are you ensuring they have space to develop in each of these areas? Are you giving them access to stakeholders? Are there clear feedback channels on what’s working and what’s not? Are you nudging them to flex their decisiveness muscle, even if they’re not the final decision maker?
Note: For an interview process, I recommend focusing on the synthesis and decisiveness questions because these will usually prompt someone to share their entire design process, meaning you don’t have to ask specific questions about observation, understanding, or creativity.
Great designers are always collecting information: what creates delight vs irritation, what lasts and what doesn’t, what do people love but not laud, what do they despise but not deride—and so on.
Great analytics engineers are constantly observing their stakeholders and symptoms, comparing human reports to objective impacts, noticing pain points that others miss, keeping an ear to the ground for opportunities, etc.
Some behavioral questions to help you probe on observational skill are:
Tell me about a time you noticed something important that others missed. How did you notice it? Why did others miss it? What was the impact?
Tell me about a time you used feedback to inform your decisions. Where did it come from? How did you choose to use it?
Observations are mere facts—they become most useful when they contribute to an understanding of the problems at hand.
This is the mental model, the internal map of systems, the invisible ledger of relationship capital.
Empathy and aptitude play equal roles in developing understanding.
This is where an analytics engineer’s purpleness really shines, where sensitive thinkers thrive, and where deep work is irreplaceable.
A deep understanding of the problem space (both technical and social) is the rich soil that fertilizes creativity.
Tell me about a time that you had to really understand your stakeholder to be successful. Why was it important to understand their perspective? How did you ensure you understood enough?
Tell me about a time you had to teach yourself about a complex system. How did you approach it? What was the result?
Observation and understanding are the groundwork from which creativity blooms.
When an opportunity or prompt arises, creativity is the skill of coming up with potential solutions to the problem.
Obvious solutions are the easiest to find—these are well-documented, industry-standard approaches to common problems. One need not be creative at all to surface these kinds of solutions.
With a little more creativity, you’ll start to see adjacent solutions—for example, borrowing an idea from grocery retail for clothing retail.
You’ll also be better able to develop an idea from a seed—you can run with a high-level suggestion instead of needing a step-by-step guide (since you’re able to generate those steps yourself).
The more creative you are, the further you’ll be able to reach in your quest for solutions, perhaps borrowing from biology or fashion in your technical pursuits.
You’ll also be able to develop ideas from more and more abstract and nebulous origins, creating your own path from A to B.
Tell me about a time you had to come up with a creative solution to a complex problem. Why did it need a creative solution? What was the impact?
Tell me about a time you applied an idea from a totally different context to your work. What inspired you to do this? What value did it add?
The more ideas you come up with, the harder your next task is: synthesis.
This is bringing everything together, pruning things down into the most important shapes. For example, you may realize that while there are dozens of methods at your disposal, there are really two philosophies: treat the symptoms or treat the root.
You’ll rule out impossible solutions and meld pieces of different ideas together into one cohesive plan.
This is the step of pros and cons, of weighing against reality. Pragmatism rules here.
Some people seem to have an instinct for this kind of thinking, which allows them to come up with logically sound conclusions at incredible speed. Always put a designer’s logic to the test, and if they’re up-to-snuff, you have a great asset on your team.
Tell me about a time you had to present several potential solutions for a problem. How did you approach this? What was the outcome?
Tell me about a time you used pros and cons to weigh potential solutions. How did you come up with pros and cons? What was the result?
For the types of folks naturally good at observation, understanding, creativity, and synthesis, often decisiveness is the design skill that takes the most intentional development.
Analytical minds are particularly prone to, well, analysis paralysis.
Here, a risk-aware mindset is helpful in breaking the lock. Often, the risk of making no decision is much greater than choosing between two viable alternatives. Let a coin flip keep things moving and you’ve won the harder battle.
Another helpful tool here is “strong opinions, weakly held”. It’s a way of forcing yourself to make a decision with the information at hand, while remaining open to changing your mind.
If you struggle with decisiveness, you’ll benefit from exploring the hard work of having an opinion.
The quality of your initial decisions may be poor—and that’s okay. The more decisions you make, the more observations you’ll build, which kicks off another design cycle. Repetition benefits you more than perfection.
Tell me about a time you had to choose between several good alternatives. How did you make the decision? How do you feel about the decision now?
Tell me about a time you made a decision that didn’t work out. Why did the decision fail? What did you do?
Every company has different approaches to job titles, leveling, and compensation, so there’s no one-size-fits-all approach to evaluating design skills.
Furthermore, different environments have more or less need for strong designers. At some companies, a senior engineer may only need mid-level design skills, while at other companies, even junior engineers are expected to have advanced design skills.
You’ll have to map these ideas back to your specific situation, but here’s a general framework:
Junior designers have major gaps in one or more areas. They’ll need others to help them understand the problem space, and they’ll focus on implementing canned solutions. Developing awareness of design generally and of the five component skills is a good goal for junior engineers.
Mid-level designers are developing enough of an understanding of the problem space to come up with an initial solution. They may appear decisive because of their tendency to deploy this first idea, but only because they lack the skill to come up with viable alternatives. Or, once they’re able to come up with viable alternatives, they’re vulnerable to analysis paralysis. Here, it’s crucial to recognize that getting stuck between viable alternatives is actually a sign of a better designer than someone who ships their first idea.
Senior designers are reliably coming up with multiple good alternatives for a problem and making effective decisions about which one to go with. Growth as a senior designer looks like increasing the scope and risk level of their design process. Understanding new topic areas, exploring new solution technologies, and making more critical decisions are all rewarding growth opportunities here.
Chances are, you’re here because you (or whoever sent this to you) observed a problem or an opportunity around assessing and developing technical talent in the data space.
If I’ve done my job well, this essay thus far has given you a deeper understanding of the component skills of design, and some questions to ask to help you go even deeper.
The next step in addressing the problem that brought you here is creativity. You’ll want to come up with some solutions, borrowing from as broad a set of inspiration as you can manage.
After that, you’ll be synthesizing those options and deciding on an action.
And then you’ll be a designer of great technical talent—whether for yourself or for your team! :)
Please tell me about what you’re creating in the comments or on Twitter @compilerqueen
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The recording will be up on YouTube soon and I’ll add that link once it’s available. If you can’t wait, you can register for Coalesce (for free!) and view the recording here.
I mean incredible in the classical sense—others might doubt their credibility because of the speed with which they weigh so many variables.